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Ezeamuzie, Ndudi O. – Journal of Educational Computing Research, 2023
Most studies suggest that students develop computational thinking (CT) through learning programming. However, when the target of CT is decoupled from programming, emerging evidence challenges the assertion of CT transferability from programming. In this study, CT was operationalized in everyday problem-solving contexts in a learning experiment (n…
Descriptors: Programming, Computer Science Education, Problem Solving, Thinking Skills
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Andrietti, Vincenzo; Su, Xuejuan – Education Economics, 2019
We propose a theory of education curricula as horizontally differentiated by their paces. The pace of a curriculum and the preparedness of a student jointly determine the match quality of the curriculum for this student, so different students derive different benefits from learning under the same curriculum. Furthermore, a change in the curricular…
Descriptors: Academic Achievement, Curriculum Design, Educational Change, Educational Quality
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Luu, King; Freeman, John G. – Computers & Education, 2011
Despite the lack of substantial evidence for improvement in the quality of teaching and learning with information and communication technology (ICT), governmental organizations have pushed ICT as a means of providing broad-scale training to meet the demand for a skilled workforce, centred upon a hypothesized ICT-scientific literacy relationship.…
Descriptors: Foreign Countries, Educational Technology, Scientific Literacy, Gender Differences
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection